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Journal of Bioinformatics and Computational Biology

Tianci Song, Yan Wang, Wei Du, Sha Cao, Yuan Tian, Yanchun Liang
Breast cancer histologic grade represents the morphological assessment of the tumor's malignancy and aggressiveness, which is vital in clinically planning treatment and estimating prognosis for patients. Therefore, the prediction of breast cancer grade can markedly elevate the detection of early breast cancer and efficiently guide its treatment. With the advent of high-throughput profiling technology, a large number of data of different types are rapidly generated, and each data provides its unique biological insight...
November 29, 2016: Journal of Bioinformatics and Computational Biology
Milos Nikolic, Tamara Stankovic, Marko Djordjevic
Accurately detecting transcription start sites (TSS) is a starting point for understanding gene transcription, and an important ingredient in a number of applications necessary for functional gene annotation, such as gene and operon predictions. Available methods for TSS detection in bacteria use very different description of the bacterial promoter structure and all of them show low accuracy. It is therefore unclear which promoter features should be included in TSS recognition, and how their accuracy impacts the search detection...
November 2, 2016: Journal of Bioinformatics and Computational Biology
Kirill E Medvedev, Nikolay A Kolchanov, Dmitry A Afonnikov
The understanding of biological and molecular mechanisms providing survival of cells under extreme temperatures and pressures will help to answer fundamental questions related to the origin of life and to design of biotechnologically important enzymes with new properties. Here, we analyze amino acid sequences of the Nip7 proteins from 35 archaeal species to identify positions containing mutations specific to the hydrostatic pressure and temperature of organism's habitat. The number of such positions related to pressure change is much lower than related to temperature change...
October 14, 2016: Journal of Bioinformatics and Computational Biology
Shuigeng Zhou, Phoebe Yi-Ping Chen, Hiroshi Mamitsuka
No abstract text is available yet for this article.
October 3, 2016: Journal of Bioinformatics and Computational Biology
Kiri Choi, Lucian P Smith, J Kyle Medley, Herbert M Sauro
MOTIVATION: Model simulation exchange has been standardized with the Simulation Experiment Description Markup Language (SED-ML), but specialized software is needed to generate simulations in this format. Text-based languages allow researchers to create and modify experimental protocols quickly and easily, and export them to a common machine-readable format. RESULTS: phraSED-ML language allows modelers to use simple text commands to encode various elements of SED-ML (models, tasks, simulations, and results) in a format easy to read and modify...
September 30, 2016: Journal of Bioinformatics and Computational Biology
Jungsoo Gim, Sungho Won, Taesung Park
High throughput sequencing technology in transcriptomics studies contribute to the understanding of gene regulation mechanism and its cellular function, but also increases a need for accurate statistical methods to assess quantitative differences between experiments. Many methods have been developed to account for the specifics of count data: non-normality, a dependence of the variance on the mean, and small sample size. Among them, the small number of samples in typical experiments is still a challenge. Here we present a method for differential analysis of count data, using conditional estimation of local pooled dispersion parameters...
September 15, 2016: Journal of Bioinformatics and Computational Biology
Naim Al Mahi, Munni Begum
One of the primary objectives of ribonucleic acid (RNA) sequencing or RNA-Seq experiment is to identify differentially expressed (DE) genes in two or more treatment conditions. It is a common practice to assume that all read counts from RNA-Seq data follow overdispersed (OD) Poisson or negative binomial (NB) distribution, which is sometimes misleading because within each condition, some genes may have unvarying transcription levels with no overdispersion. In such a case, it is more appropriate and logical to consider two sets of genes: OD and non-overdispersed (NOD)...
September 15, 2016: Journal of Bioinformatics and Computational Biology
Li Gu, Lichun Xue, Qi Song, Fengji Wang, Huaqin He, Zhongyi Zhang
During commercial transactions, the quality of flue-cured tobacco leaves must be characterized efficiently, and the evaluation system should be easily transferable across different traders. However, there are over 3000 chemical compounds in flue-cured tobacco leaves; thus, it is impossible to evaluate the quality of flue-cured tobacco leaves using all the chemical compounds. In this paper, we used Support Vector Machine (SVM) algorithm together with 22 chemical compounds selected by ReliefF-Particle Swarm Optimization (R-PSO) to classify the fragrant style of flue-cured tobacco leaves, where the Accuracy (ACC) and Matthews Correlation Coefficient (MCC) were 90...
September 9, 2016: Journal of Bioinformatics and Computational Biology
Beichuan Deng, Seongho Kim, Hengguang Li, Elisabeth Heath, Xiang Zhang
Comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC[Formula: see text][Formula: see text][Formula: see text]GC-MS) has been used to analyze multiple samples in a metabolomics study. However, due to some uncontrollable experimental conditions, such as the differences in temperature or pressure, matrix effects on samples and stationary phase degradation, there is always a shift of retention times in the two GC columns between samples. In order to correct the retention time shifts in GC[Formula: see text][Formula: see text][Formula: see text]GC-MS, the peak alignment is a crucial data analysis step to recognize the peaks generated by the same metabolite in different samples...
September 9, 2016: Journal of Bioinformatics and Computational Biology
Wilson Wen Bin Goh, Limsoon Wong
In proteomics, useful signal may be unobserved or lost due to the lack of confident peptide-spectral matches. Selection of differential spectra, followed by associative peptide/protein mapping may be a complementary strategy for improving sensitivity and comprehensiveness of analysis (spectra-first paradigm). This approach is complementary to the standard approach where functional analysis is performed only on the finalized protein list assembled from identified peptides from the spectra (protein-first paradigm)...
October 2016: Journal of Bioinformatics and Computational Biology
Kento Kodama, Hiroto Saigo
Despite the accumulation of quantitative trait loci (QTL) data in many complex human diseases, most of current approaches that have attempted to relate genotype to phenotype have achieved limited success, and genetic factors of many common diseases are yet remained to be elucidated. One of the reasons that makes this problem complex is the existence of single nucleotide polymorphism (SNP) interaction, or epistasis. Due to excessive amount of computation for searching the combinatorial space, existing approaches cannot fully incorporate high-order SNP interactions into their models, but limit themselves to detecting only lower-order SNP interactions...
October 2016: Journal of Bioinformatics and Computational Biology
Sohee Oh, Iksoo Huh, Seung Yeoun Lee, Taesung Park
Most genome-wide association studies (GWAS) have been conducted by focusing on one phenotype of interest for identifying genetic variants associated with common complex phenotypes. However, despite many successful results from GWAS, only a small number of genetic variants tend to be identified and replicated given a very stringent genome-wide significance criterion, and explain only a small fraction of phenotype heritability. In order to improve power by using more information from data, we propose an alternative multivariate approach, which considers multiple related phenotypes simultaneously...
October 2016: Journal of Bioinformatics and Computational Biology
Ana B Pavel, Cristian I Vasile
Cancer is a complex and heterogeneous genetic disease. Different mutations and dysregulated molecular mechanisms alter the pathways that lead to cell proliferation. In this paper, we explore a method which classifies genes into oncogenes (ONGs) and tumor suppressors. We optimize this method to identify specific (ONGs) and tumor suppressors for breast cancer, lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) and colon adenocarcinoma (COAD), using data from the cancer genome atlas (TCGA). A set of genes were previously classified as ONGs and tumor suppressors across multiple cancer types (Science 2013)...
August 31, 2016: Journal of Bioinformatics and Computational Biology
Fangzhou Shen, Jian Li, Ying Zhu, Zhuo Wang
Cancer cells have different metabolism in contrast to normal cells. The advancement in omics measurement technology enables the genome-wide characterization of altered cellular processes in cancers, but the metabolic flux landscape of cancer is still far from understood. In this study, we compared the well-reconstructed tissue-specific models of five cancers, including breast, liver, lung, renal, and urothelial cancer, and their corresponding normal cells. There are similar patterns in majority of significantly regulated pathways and enriched pathways in correlated reaction sets...
August 29, 2016: Journal of Bioinformatics and Computational Biology
Jinwoo Park, Benjamin Hur, Sungmin Rhee, Sangsoo Lim, Min-Su Kim, Kwangsoo Kim, Wonshik Han, Sun Kim
A breast cancer subtype classification scheme, PAM50, based on genetic information is widely accepted for clinical applications. On the other hands, experimental cancer biology studies have been successful in revealing the mechanisms of breast cancer and now the hallmarks of cancer have been determined to explain the core mechanisms of tumorigenesis. Thus, it is important to understand how the breast cancer subtypes are related to the cancer core mechanisms, but multiple studies are yet to address the hallmarks of breast cancer subtypes...
August 29, 2016: Journal of Bioinformatics and Computational Biology
Wilson Wen Bin Goh, Limsoon Wong
Identifying reproducible yet relevant features is a major challenge in biological research. This is well documented in genomics data. Using a proposed set of three reliability benchmarks, we find that this issue exists also in proteomics for commonly used feature-selection methods, e.g. [Formula: see text]-test and recursive feature elimination. Moreover, due to high test variability, selecting the top proteins based on [Formula: see text]-value ranks - even when restricted to high-abundance proteins - does not improve reproducibility...
August 3, 2016: Journal of Bioinformatics and Computational Biology
Nada Abidi, Raimo Franke, Peter Findeisen, Frank Klawonn
To better understand the dynamics of the underlying processes in cells, it is necessary to take measurements over a time course. Modern high-throughput technologies are often used for this purpose to measure the behavior of cell products like metabolites, peptides, proteins, [Formula: see text]RNA or mRNA at different points in time. Compared to classical time series, the number of time points is usually very limited and the measurements are taken at irregular time intervals. The main reasons for this are the costs of the experiments and the fact that the dynamic behavior usually shows a strong reaction and fast changes shortly after a stimulus and then slowly converges to a certain stable state...
August 3, 2016: Journal of Bioinformatics and Computational Biology
Artem Petrov, Vladimir Arzhanik, Gennady Makarov, Oleg Koliasnikov
Antibodies are the family of proteins, which are responsible for antigen recognition. The computational modeling of interaction between an antigen and an antibody is very important when crystallographic structure is unavailable. In this research, we have discovered the correlation between the amino acid sequence of antibody and its specific binding characteristics on the example of the novel conservative binding motif, which consists of four residues: Arg H52, Tyr H33, Thr H59, and Glu H61. These residues are specifically oriented in the binding site and interact with each other in a specific manner...
August 2016: Journal of Bioinformatics and Computational Biology
Javier González, Alberto Muñoz, Gabriel Martos
We propose a new method to visualize gene expression experiments inspired by the latent semantic indexing technique originally proposed in the textual analysis context. By using the correspondence word-gene document-experiment, we define an asymmetric similarity measure of association for genes that accounts for potential hierarchies in the data, the key to obtain meaningful gene mappings. We use the polar decomposition to obtain the sources of asymmetry of the similarity matrix, which are later combined with previous knowledge...
August 2016: Journal of Bioinformatics and Computational Biology
Daniel Cerqueda-García, Luisa I Falcón
Microbialites and microbial mats are complex communities with high phylogenetic diversity. These communities are mostly composed of bacteria and archaea, which are the earliest living forms on Earth and relevant to biogeochemical evolution. In this study, we identified the shared metabolic pathways for uptake of inorganic C and N in microbial mats and microbialites based on metagenomic data sets. An in silico analysis for autotrophic pathways was used to trace the paths of C and N to the system, following an elementary flux modes (EFM) approach, resulting in a stoichiometric model...
August 2016: Journal of Bioinformatics and Computational Biology
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